Array technologies have been widely used in biomedical studies for the detection of biomolecules and profiling of gene expression levels, etc. Arrays are typically comprised of immobilized probes which can bind to or hybridize with target molecules in a sample. Detection of binding or hybridization events is often achieved through the use of optical labels (e.g. fluorophores) and scanning or imaging techniques (e.g. fluorescence scanning or imaging). A feature on an array is a small region of immobilized probes that are specific for a given target molecule, e.g. probes that hybridize to specific DNA or RNA sequences. Identifying the pattern of labeled features on a hybridized array thus provides information about specific molecules, e.g. DNA or RNA molecules in the sample, which in turn can provide valuable data in biomedical studies. Two important engineering requirements for providing high quality, quantitative data for biomedical investigations are (i) to correctly image the hybridized arrays, and (ii) to correctly analyze the images to extract quantitative data. Existing optical imaging systems typically image one region of an array at a time, which can be a slow process if a number of different regions need to be imaged. In addition, current methods of image analysis typically determine a signal intensity level (i.e. an analog quantity) for each array feature. Intensity level measurements are often subject to a variety of instrumental drift and analysis errors, therefore improved methods for determining whether or not target molecules are bound to a given array feature, and improved methods for transforming that data into quantitative measures of the number of target molecules present in a sample, are of great importance to expanding the use of array technologies in biomedical applications.